11.According to the equation of the shown model, in which type of unit is the impact of the program most sensitive to the size of the hospital? a)In ICU units. b)In PEDIATRIC units. c)In NON_ICU units. d)Sensitivity to size is the same for all types of units. e)In ICU units of large hospitals.
Questions 12-18 Εmployees at a financial company earn annual commissions, measured in thousands of dollars, by signing up clients. The company is interested in identifying the characteristics of the employees who sign up many clients and earn large commissions. Three possible variables are considered as predictors of performance: Score on a training program (0 to 100 point scale), years of experience in the industry ( Yrs Experience ), and the number of years of education post high school ( Education ). Correlations Commissions Score Yrs Experience Education Commissions 1.0000 0.5415 -0.4193 0.4713 Score 0.5415 1.0000 -0.9012 0.6009 Yrs Experience -0.4193 -0.9012 1.0000 -0.5437 Education 0.4713 0.6009 -0.5437 1.0000 Summary of Fit RSquare 0.352089 Root Mean Square Error 7.769735 Mean of Response 39.915 Observations (or Sum Wgts) 400 Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Model 3 12991.072 4330.36 71.7317 Error 396 23906.038 60.37 Prob > F C. Total 399 36897.110 <.0001* Parameter Estimates Term Estimate Std Error t Ratio Prob>|t| Intercept -8.176562 7.243549 -1.13 0.2597 Score 0.5424163 0.072261 7.51 <.0001* Yrs Experience 0.5048152 0.127883 3.95 <.0001* Education 1.6721834 0.368509 4.54 <.0001*
12.The average number of years of experience for these employees is about 13.Ignoring Scoreand Education, employees with about 30 years of experience 14.The strongest linear association is between 15.The overall F-ratio indicates, if we accept the assumptions of the multiple regression model, that a)RemovingEducationfrom the model would significantly reduce R2. b)Adding each of these predictors improved the R2significantly. c)Each of the predictors is significantly different from zero. d)These predictors collectively explain significant variation in commissions. e)The model suffers from severe collinearity.
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